Impairment of alertness in vehicle operators poses a danger not only to themselves but also often to the public at large. Thousands of deaths and injuries result each year that are fatigue related. Moreover, the financial costs as a result of the injuries and deaths are prohibitive. As a result, significant efforts have been made in the area of vigilance monitoring of the operator of a vehicle to detect the decrease in attention of the operator due to drowsiness and to alert her/him.
Conventional driver vigilance monitoring techniques fall within the following broad classes: (1) image acquisition and processing of facial features such as eye and head movements; (2) image acquisition and processing of road lane maintaining capability and (3) monitoring of the physiological responses of the body while driving.
However, there are several limitations with the existing technologies. A vigilance monitoring techniques based on monitoring physiological responses of the body like EEG and ECG, are intrusive, expensive and can distract or cause annoyance to the driver. In US 2004/0044293, for example, a system for monitoring, recording and/or analysing vigilance, alertness or wakefulness and/or a stressed state of an operator of equipment or machinery in a variety of situations including situations wherein the degree of vigilance of the operator has implications for the safety or well being of the operator or other persons.
The monitoring system according to US 2004/0044293 is designed, inter alia, to provide non-invasive monitoring of a driver's physiological data including movement activity, heart activity, respiration and other physiological functions. The monitored physiological data may undergo specific analysis processing to assist in determining of the driver's state of vigilance. The system is designed to detect various states of the driver's activity and detect certain conditions of driver fatigue or relaxation state that could lead to an unsafe driving condition or conditions.
The system includes means for gathering movement data associated with the driver including a plurality of sensors such as touch sensitive mats placed in locations of the vehicle that make contact with the driver, such as the seat, steering wheel, pedal(s), seat belt or the like. Each location may include several sensors or mats to more accurately monitor movements of the driver.
A processing means may be programmed to recognize particular movement signatures or patterns of movement, driver posture or profile and to interpret these to indicate that vigilance has deteriorated or is below an acceptable threshold. The sensors or mats may include piezoelectric, electrostatic, piezo ceramic or strain gauge material.
Moreover, lane tracking methods require visible lane markings and even if present are significantly impaired by snow, rain, hail, and/or dirt existing on the road. Nighttime and misty conditions are also impairments.
Existing image processing techniques used to track eyes and head patterns to track lane maintaining capability necessarily require expensive (both cost and computational requirement-wise) hardware to operate and are highly dependent on factors such as, the relative position of the driver's head with respect to the sensors, illumination, and facial features and/or mental state of the driver, whether happy, anxious, or angry. Each of these indicators suffers from a relatively low probability of detecting drowsiness. Many of the measurements for indicating drowsiness do not adequately represent the responsiveness of the driver because of such influences as road conditions, patterns and vehicle type. Moreover, the cost for these techniques is often prohibitive. Even yet, more often than not, the existing techniques detect drowsiness when it may be too late for accident prevention purposes.
In US 2007/0080816, a vigilance monitoring system for alerting a driver of a vehicle upon detecting a state of drowsiness by calculation of a deviation between a time derivative of force and/or displacement exerted by the driver on a driver-vehicle interface, e.g., the steering wheel or the gas pedal, and a moving average for the time derivative of force and/or displacement to thereby quantify the state of drowsiness of the driver independent of conditions inside and outside the vehicle is disclosed. The system includes a sensor connected to at least one driver-vehicle interface to monitor force on and/or displacement of the driver-vehicle interface.
The system also includes an intelligent control in communication with the sensor as well as a time derivative profile modeled from the time derivative of force and/or displacement using the intelligent control. Included also is a general trend modeled from the moving average of the time derivative of force and/or displacement using the intelligent control. In addition, the system includes a spikiness index defined by a degree of deviation between the time derivative profile and the general trend to thereby quantify the state of drowsiness of the driver independent of conditions inside and outside of the vehicle. However, the system according to US 2007/0080816 may require extensive processsing capabilities in order to compute the data needed for the determination of the state of drowsiness.
In light of the problems encountered within the prior art, there is a continuing need for improved systems and methods that are capable of detecting drowsiness under different and varying conditions such as under varying light conditions, varying weather conditions and varying road conditions, for a diversity of driver physionomies and under the influence of other potentially disturbing factors such as usage of glasses etc., with a high degree of accuracy and reliability.